Transcriptomic exploration combined with experimental validation: uncovering the potential value of biomarkers related to ammonia-induced cell death in hepatic ischemia-reperfusion injury.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41299729", "kind": "science-record", "revision": 3, "content_hash": "sha256:b49c14b8d19f3559efc44a991ec011f6d0482c3138ce51e3efd2de376e002a5e", "created_at": "2026-11-01T20:31:19Z", "updated_at": "2026-11-01T22:15:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptomic exploration combined with experimental validation: uncovering the potential value of biomarkers related to ammonia-induced cell death in hepatic ischemia-reperfusion injury.", "doi": "10.1186/s40001-025-03450-1", "pmid": "41299729", "authors": ["Runyu Zhuang", "Junhao Xiao", "Benliang Mao", "Yong Yan", "Wei Yuan", "Fan Wu", "Bailin Wang"], "journal": "European journal of medical research", "year": 2025, "abstract": "BACKGROUND: Hepatic ischemia-reperfusion injury (HIRI) represents the leading cause of postoperative liver dysfunction and failure. Ammonia-induced cell death (ACD), defined by lysosomal and mitochondrial disruption due to intracellular ammonia accumulation, appears to contribute to the pathogenesis of HIRI.\nMETHODS: Transcriptomic datasets GSE151648 and GSE12720 were retrieved from the Gene Expression Omnibus (GEO), and 467 ACD-related genes were compiled from published reports. Differential expression analysis combined with Weighted Gene Co-expression Network Analysis (WGCNA) was applied to identify candidate genes and assess their functional relevance. Biomarkers closely associated with HIRI were subsequently determined through protein-protein interaction (PPI) network construction, machine learning approaches, and expression validation. A nomogram was then established based on these biomarkers, followed by Gene Set Enrichment Analysis (GSEA), immune infiltration profiling, and network prediction. Furthermore, single-cell analysis was employed to investigate the expression of biomarkers across different cell types. Finally, liver tissues from HIRI mouse models were examined to confirm biomarker expression.\nRESULTS: A total of 586 differentially expressed genes intersected with 762 key module genes, yielding 39 candidates primarily enriched in inflammatory signaling pathways. Among these, LCP1, SLC16A3, and RGS2 emerged as biomarkers, each markedly upregulated in HIRI samples. The biomarker-based nomogram demonstrated robust diagnostic accuracy. Enrichment analyses indicated that the biomarkers were closely related to immune and metabolic pathways. Consistently, immune cell infiltration and immune functions were elevated in HIRI samples and correlated significantly with biomarker expression. Concurrently, single-cell analysis revealed that all three biomarkers were expressed within mononuclear phagocytes, with their expression levels exhibiting significant differences between the HIRI group and the control group. Moreover, multiple miRNAs and lncRNAs were predicted to interact with the identified biomarkers. Validation in HIRI mouse liver tissues confirmed consistency with transcriptomic findings.\nCONCLUSION: LCP1, SLC16A3, and RGS2 have been identified as biomarkers of HIRI. The study advances understanding of ACD-related genes signatures in HIRI and provides a foundation for future mechanistic research and therapeutic development.", "claims": [{"id": "claim-method", "statement": "Intergroup comparisons were assessed with the Wilcoxon test, applying a significance threshold of P < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41299729", "locator": "sections[16] \"Statistical analysis\" paragraph 2", "quote": "Intergroup comparisons were assessed with the Wilcoxon test, applying a significance threshold of P < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The dataset(s) supporting the conclusions of this article is(are) available in the [GEO] at [https://www.ncbi.nlm.nih.gov/gds] with accession numbers (GSE151648，GSE171539 and GSE12720), [MSigDB] at [https://www.gsea-msigdb.org/gsea/msigdb].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41299729", "locator": "sections[35] \"Data availability\" paragraph 2", "quote": "The dataset(s) supporting the conclusions of this article is(are) available in the [GEO] at [https://www.ncbi.nlm.nih.gov/gds] with accession numbers (GSE151648，GSE171539 and GSE12720), [MSigDB] at [https://www.gsea-msigdb.org/gsea/msigdb]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "LCP1, SLC16A3, and RGS2 have been identified as biomarkers of HIRI.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41299729", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "LCP1, SLC16A3, and RGS2 have been identified as biomarkers of HIRI."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "LCP1, SLC16A3, and RGS2 have been identified as biomarkers of HIRI.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41299729"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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